The subject matter discussed in the background section is not to be assumed as prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section is not assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to claimed embodiments.
In the context of computing, scheduling is the method by which specified workloads are assigned to resources which are then responsible for completing the workloads. Such workloads may be, for example, virtual computation elements such as threads, processes, and data flows. The scheduling process applies available hardware resources such as processors, memory, hard drive space, network links, network addresses or IP (Internet Protocol) addresses, expansion cards, and so forth.
A scheduler responsible for performing the scheduling processes and generally will seek to perform a variety of functions in addition to scheduling work, such as optimizing utilizing of resources through a load balancing process which thus permits multiple users to share system resources more effectively.
Implementation of a scheduler is a technically complex task as there exist many criteria which affect operation of the scheduler and may in turn affect perceived performance of the underlying computing resources based on how the scheduler allocates resources and prioritizes competing needs.
Unfortunately, conventional schedulers fail to adequately address the needs of specified Quality of Service (QoS) targets or Service Level Targets (SLTs) such as those defining an exemplary 95th percentile expected completion time and resource usage for a given task. Moreover, it may be impossible to prove the correctness of a scheduling algorithm implemented by conventional schedulers as they generally lack sufficient extendibility and maintainability criteria.
The present state of the art may therefore benefit from the variously disclosed schedulers including the systems, methods, and apparatuses for implementing: (i) the stateless, deterministic scheduler and work discovery system with interruption recovery which is described herein; (ii) the scalable scheduler with heterogeneous resource allocation of large competing workloads types using Quality of Service (QoS) requirements which is described herein; and (iii) the scheduler with preemptive termination of existing workloads to free resources for high priority items, which is also described herein. Each of the described scheduler means are additionally operable within a cloud based computing environment in accordance with the described embodiments set forth below.